REMIND-D: A Hybrid Energy-Economy Model of Germany

This paper presents a detailed documentation of the hybrid energy-economy model REMIND-D. REMIND-D is a Ramsey-type growth model for Germany that integrates a detailed bottom-up energy system module, coupled by a hard link. The model provides a quantitative framework for analyzing long-term domestic CO2 emission reduction scenarios. Due to its hybrid nature, REMIND-D facilitates an integrated analysis of the interplay between technological mitigation options in the different sectors of the energy system as well as overall macroeconomic dynamics. REMIND-D is an intertemporal optimization model, featuring optimal annual mitigation effort and technology deployment as a model output. In order to provide transparency on model assumptions, this paper gives an overview of the model structure, the input data used to calibrate REMIND-D to the Federal Republic of Germany, as well as the techno-economic parameters of the technologies considered in the energy system module.Hybrid Model, Germany, Energy System, Domestic Mitigation

Sleep-like slow oscillations improve visual classification through synaptic homeostasis and memory association in a thalamo-cortical model

The occurrence of sleep passed through the evolutionary sieve and is widespread in animal species. Sleep is known to be beneficial to cognitive and mnemonic tasks, while chronic sleep deprivation is detrimental. Despite the importance of the phenomenon, a complete understanding of its functions and underlying mechanisms is still lacking. In this paper, we show interesting effects of deep-sleep-like slow oscillation activity on a simplified thalamo-cortical model which is trained to encode, retrieve and classify images of handwritten digits. During slow oscillations, spike-timing-dependent-plasticity (STDP) produces a differential homeostatic process. It is characterized by both a specific unsupervised enhancement of connections among groups of neurons associated to instances of the same class (digit) and a simultaneous down-regulation of stronger synapses created by the training. This hierarchical organization of post-sleep internal representations favours higher performances in retrieval and classification tasks. The mechanism is based on the interaction between top-down cortico-thalamic predictions and bottom-up thalamo-cortical projections during deep-sleep-like slow oscillations. Indeed, when learned patterns are replayed during sleep, cortico-thalamo-cortical connections favour the activation of other neurons coding for similar thalamic inputs, promoting their association. Such mechanism hints at possible applications to artificial learning systems.Comment: 11 pages, 5 figures, v5 is the final version published on Scientific Reports journa

Optimized energy management of inductively charged electric buses reflecting operational constraints and traffic conditions

The introduction of alternative propulsion concepts in public transport makes significant contributions to further reduce pollutants emitted by transport systems (noise, air pollutants). This paradigm shift is a major challenge for public transport operators. Operational performance of heavy duty vehicles depends on many different factors such as climatic conditions, load profiles (e.g. variations in passenger occupancy) and track topology. Currently there is no common standard which allows the assessment of energetic performance of different vehicle concepts and optimum deployment strategies of electric charging infrastructure in the network (with respect to their impact on the vehicles’ duty plans). This paper introduces a simulation-based approach to provide answers to this multi-variant optimization problem. The model outlined in this paper allows operators to choose the most adequate vehicle type(s) and corresponding infrastructure for their respective conditions aiming at a maximum operational availability of the buses during the operational day. Furthermore, the simulation model allows the assessment of time tables and line topologies with respect to their operational feasibility. This paper discusses experiences made with simulative studies in the introduction of inductively charged electric buses in the city of Braunschweig (Germany)